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Medical image processing on the GPU - past, present and future.
Med Image Anal. 2013 Dec; 17(8):1073-94.MI

Abstract

Graphics processing units (GPUs) are used today in a wide range of applications, mainly because they can dramatically accelerate parallel computing, are affordable and energy efficient. In the field of medical imaging, GPUs are in some cases crucial for enabling practical use of computationally demanding algorithms. This review presents the past and present work on GPU accelerated medical image processing, and is meant to serve as an overview and introduction to existing GPU implementations. The review covers GPU acceleration of basic image processing operations (filtering, interpolation, histogram estimation and distance transforms), the most commonly used algorithms in medical imaging (image registration, image segmentation and image denoising) and algorithms that are specific to individual modalities (CT, PET, SPECT, MRI, fMRI, DTI, ultrasound, optical imaging and microscopy). The review ends by highlighting some future possibilities and challenges.

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Publisher Full Text (DOI)

Authors+Show Affiliations

Eklund A
Virginia Tech Carilion Research Institute, Virginia Tech, Roanoke, USA. Electronic address: andek034@gmail.com.
Dufort P
No affiliation info available
Forsberg D
No affiliation info available
LaConte SM
No affiliation info available

MeSH

AlgorithmsComputer GraphicsEquipment DesignImage Interpretation, Computer-AssistedReproducibility of ResultsSensitivity and SpecificitySignal Processing, Computer-Assisted

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't
Review

Language

eng

PubMed ID

23906631

Citation

Eklund, Anders, et al. "Medical Image Processing On the GPU - Past, Present and Future." Medical Image Analysis, vol. 17, no. 8, 2013, pp. 1073-94.
Eklund A, Dufort P, Forsberg D, et al. Medical image processing on the GPU - past, present and future. Med Image Anal. 2013;17(8):1073-94.
Eklund, A., Dufort, P., Forsberg, D., & LaConte, S. M. (2013). Medical image processing on the GPU - past, present and future. Medical Image Analysis, 17(8), 1073-94. https://doi.org/10.1016/j.media.2013.05.008
Eklund A, et al. Medical Image Processing On the GPU - Past, Present and Future. Med Image Anal. 2013;17(8):1073-94. PubMed PMID: 23906631.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Medical image processing on the GPU - past, present and future. AU - Eklund,Anders, AU - Dufort,Paul, AU - Forsberg,Daniel, AU - LaConte,Stephen M, Y1 - 2013/06/05/ PY - 2012/10/12/received PY - 2013/05/07/revised PY - 2013/05/22/accepted PY - 2013/8/3/entrez PY - 2013/8/3/pubmed PY - 2014/7/1/medline KW - CUDA KW - Graphics processing unit (GPU) KW - Image processing KW - Image reconstruction KW - Medical imaging SP - 1073 EP - 94 JF - Medical image analysis JO - Med Image Anal VL - 17 IS - 8 N2 - Graphics processing units (GPUs) are used today in a wide range of applications, mainly because they can dramatically accelerate parallel computing, are affordable and energy efficient. In the field of medical imaging, GPUs are in some cases crucial for enabling practical use of computationally demanding algorithms. This review presents the past and present work on GPU accelerated medical image processing, and is meant to serve as an overview and introduction to existing GPU implementations. The review covers GPU acceleration of basic image processing operations (filtering, interpolation, histogram estimation and distance transforms), the most commonly used algorithms in medical imaging (image registration, image segmentation and image denoising) and algorithms that are specific to individual modalities (CT, PET, SPECT, MRI, fMRI, DTI, ultrasound, optical imaging and microscopy). The review ends by highlighting some future possibilities and challenges. SN - 1361-8423 UR - https://www.unboundmedicine.com/medline/citation/23906631/Medical_image_processing_on_the_GPU___past_present_and_future_ DB - PRIME DP - Unbound Medicine ER -